Quantifying Electronic Health Record Data: A Potential Risk for Cognitive Overload

Abstract

OBJECTIVES: To quantify and describe patient-generated health data. METHODS: This is a retrospective, single-center study of patients hospitalized in the pediatric cardiovascular ICU between February 1, 2020, and February 15, 2020. The number of data points generated over a 24-hour period per patient was collected from the electronic health record. Data were analyzed by type, and frontline provider exposure to data was extrapolated on the basis of patient-to-provider ratios. RESULTS: Thirty patients were eligible for inclusion. Nineteen were hospitalized after cardiac surgery, whereas 11 were medical patients. Patients generated an average of 1460 (SD 509) new data points daily, resulting in frontline providers being presented with an average of 4380 data points during a day shift (7:00 am to 7:00 pm). Overnight, because of a higher patient-to-provider ratio, frontline providers were exposed to an average of 16 060 data points. There was no difference in data generation between medical and surgical patients. Structured data accounted for >80% of the new data generated. CONCLUSIONS: Health care providers face significant generation of new data daily through the contemporary electronic health record, likely contributing to cognitive burden and putting them at risk for cognitive overload. This study represents the first attempt to quantify this volume in the pediatric setting. Most data generated are structured and amenable to data-optimization systems to mitigate the potential for cognitive overload and its deleterious effects on patient safety and health care provider well-being.